import streamlit as st

from PIL import Image
from tool_loader import ToolLoader
from app_user_desc import app_user_desc
from app_dev_desc import app_dev_desc
from logger import log_response
from logger import log_enabled
from app_chat import app_chat
import numpy as np

from app_agent_config import AgentConfig 

# Create an instance of AgentConfig
agent_config = AgentConfig()

global image

# Declare global variable

st.set_page_config(
    page_title="Transformers can realy do anything...",
    page_icon="👋",
)

st.title("Hugging Face Agent and tools")

## LB https://huggingface.co/spaces/qiantong-xu/toolbench-leaderboard

st.markdown("Welcome to the Hugging Face Agent and Tools app! This app allows you to interact with various tools using the Hugging Face API.")

#######

import pandas as pd
from io import StringIO
with st.sidebar:
    with st.expander("See explanation"):
    
        img_file_buffer = st.file_uploader('Upload a PNG image', type='png')
        if img_file_buffer is not None:
            image_raw = Image.open(img_file_buffer)
            #global image
            image = np.array(image_raw)
            ######## 
            st.image(image)
            
        uploaded_file = st.file_uploader("Choose a file", type='pdf')
        if uploaded_file is not None:
            # To read file as bytes:
            pdf_document = uploaded_file.getvalue()
            global document
            document = pdf_document
            st.write(pdf_document)
            
        uploaded_txt_file = st.file_uploader("Choose a file", type='txt')
        if uploaded_txt_file is not None:
            # To read file as bytes:
            txt_document = uploaded_txt_file.getvalue()
            document = txt_document
            st.write(txt_document)
            
        uploaded_csv_file = st.file_uploader("Choose a file", type='csv')
        if uploaded_csv_file is not None:
            # To read file as bytes:
            csv_document = uploaded_csv_file.getvalue()
            document = csv_document
            st.write(csv_document)
        
            # To convert to a string based IO:
            #stringio = StringIO(uploaded_file.getvalue().decode("utf-8"))
            #st.write(stringio)
        
            # To read file as string:
            #string_data = stringio.read()
            #st.write(string_data)
        
            # Can be used wherever a "file-like" object is accepted:
            dataframe = pd.read_csv(uploaded_file)
            st.write(dataframe)
    


# Create a page with tabs
tabs = st.tabs(["Chat", "URL, Tools and logging", "User Description", "Developers"])

# Tab 1: Chat
with tabs[0]:
    
    # Code for URL and Tools checkboxes 
    #chat_description()
    # Examples for the user perspective
    st.markdown("Stat to chat. e.g. Generate an image of a boat. This will make the agent use the tool text2image to generate an image.")
 
# Tab 2: URL and Tools
with tabs[1]:
    #
    agent_config.configure()

# Tab 3: User Description
#with tabs[2]:
    #
#    app_user_desc()
    
# Tab 4: Developers
#with tabs[3]:
#    app_dev_desc()     
   
#app_chat()    
app_chat(agent_config)